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Record W2613830765 · doi:10.1021/acssuschemeng.7b00976

Direct Conversion of the Oleaginous Yeast<i>Rhodosporidium diobovatum</i>to Biodiesel Using the Ionic Liquid [C<sub>2</sub>mim][EtSO<sub>4</sub>]

2017· article· en· W2613830765 on OpenAlexafffund
Valerie C. A. Ward, Garret Munch, Nazim Çiçek, Lars Rehmann

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of ManitobaWestern University
FundersNational Renewable Energy LaboratoryNatural Sciences and Engineering Research Council of CanadaUniversity of California, DavisCanada Foundation for InnovationBioFuelNet CanadaAlexander von Humboldt-Stiftung
KeywordsIonic liquidTransesterificationMethanolYield (engineering)BiodieselYeastCatalysisChemistryPotassium hydroxideFatty acid methyl esterBiomass (ecology)Nuclear chemistryOrganic chemistryMaterials scienceBiochemistryBiologyAgronomy

Abstract

fetched live from OpenAlex

In this study, the direct conversion of wet oleaginous yeast biomass to fatty acid methyl esters (FAME) using base transesterification in the presence of an ionic liquid was optimized. The ionic liquid, 1-ethyl-3-methylimidazolium ethylsulfate, was used to facilitate this process and improved the yields of FAME transesterified directly from wet biomass using potassium hydroxide (KOH) as a catalyst. Factorial screening was first used to identify critical factors affecting the transesterification yield, and subsequently, response surface methodology was employed to study the interaction of methanol, KOH, and temperature on reaction yield. The optimized conditions for dried biomass were found to be 16.9 g methanol/g yeast, 0.056 g KOH/g yeast, 2 g [C 2 mim[EtSO 4 ]/g yeast, and 65 °C, which yielded 97.1% conversion of the maximum FAME yield in only 2.5 h. The optimized system was further studied to observe the reaction profiles and FAME yield over time from both dry yeast and fresh wet yeast biomass containing varying degrees of water (from 65 to 80 wt %). The ionic liquid was found to improve total overall yield of FAME (96.9 ± 0.4%) compared to the negative control without ionic liquid (69.6 ± 5.0%) when wet yeast was used. While all the ionic liquid was recovered from the reaction, it contained only 59.3% of the catalyst, suggesting a heterogeneous catalyst may be more appropriate in future work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.198
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2017
Admission routes2
Has abstractyes

Explore more

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